Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 939 780 893 377 447 190 876 884 493 223 257 361 294 250 66 320 73 792 166 521
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 361 250 73 NA NA 166 190 320 66 NA 257 876 521 493 780 884 377 447 893 792 223 939 294
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 1 3 1 5 2 3 4 5 5
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "o" "b" "y" "u" "t" "E" "I" "C" "X" "T"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 1
which( manyNumbersWithNA > 900 )
[1] 22
which( is.na( manyNumbersWithNA ) )
[1] 4 5 10
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 939
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 939
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 939
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "E" "I" "C" "X" "T"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "o" "b" "y" "u" "t"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 4 5 9 12 16 20
sum( manyNumbers %in% 300:600 )
[1] 6
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "small" "small" NA NA "small" "small" "small" "small" NA "small" "large" "large" "small" "large" "large" "small"
[18] "small" "large" "large" "small" "large" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "small" "small" "UNKNOWN" "UNKNOWN" "small" "small" "small" "small" "UNKNOWN" "small" "large" "large"
[14] "small" "large" "large" "small" "small" "large" "large" "small" "large" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 0 0 NA NA 0 0 0 0 NA 0 876 521 0 780 884 0 0 893 792 0 939 0
unique( duplicatedNumbers )
[1] 2 1 3 5 4
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 1 3 5 4
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE FALSE TRUE TRUE FALSE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 22
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 939
which.min( manyNumbersWithNA )
[1] 9
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 66
range( manyNumbersWithNA, na.rm = TRUE )
[1] 66 939
manyNumbersWithNA
[1] 361 250 73 NA NA 166 190 320 66 NA 257 876 521 493 780 884 377 447 893 792 223 939 294
sort( manyNumbersWithNA )
[1] 66 73 166 190 223 250 257 294 320 361 377 447 493 521 780 792 876 884 893 939
sort( manyNumbersWithNA, na.last = TRUE )
[1] 66 73 166 190 223 250 257 294 320 361 377 447 493 521 780 792 876 884 893 939 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 939 893 884 876 792 780 521 493 447 377 361 320 294 257 250 223 190 166 73 66 NA NA NA
manyNumbersWithNA[1:5]
[1] 361 250 73 NA NA
order( manyNumbersWithNA[1:5] )
[1] 3 2 1 4 5
rank( manyNumbersWithNA[1:5] )
[1] 3 2 1 4 5
sort( mixedLetters )
[1] "b" "C" "E" "I" "o" "t" "T" "u" "X" "y"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 9 5 5 5 9 2 5 1 5 9
rank( manyDuplicates, ties.method = "min" )
[1] 8 3 3 3 8 2 3 1 3 8
rank( manyDuplicates, ties.method = "random" )
[1] 9 5 3 4 10 2 6 1 7 8
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 -2.0878073 -1.6958239 1.2073455 -0.8685920 -0.0354016 0.8246834 0.9928578
[13] 0.9644480 0.2046025 1.3021420
round( v, 0 )
[1] -1 0 0 0 1 -2 -2 1 -1 0 1 1 1 0 1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -2.1 -1.7 1.2 -0.9 0.0 0.8 1.0 1.0 0.2 1.3
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -2.09 -1.70 1.21 -0.87 -0.04 0.82 0.99 0.96 0.20 1.30
floor( v )
[1] -1 -1 0 0 1 -3 -2 1 -1 -1 0 0 0 0 1
ceiling( v )
[1] -1 0 0 1 1 -2 -1 2 0 0 1 1 1 1 2
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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